import sys, os
sys.path.append(os.path.join(os.getcwd(), '../'))
from pymining.math.matrix import Matrix
from pymining.math.text2matrix import Text2Matrix
from pymining.nlp.segmenter import Segmenter
from pymining.common.global_info import GlobalInfo
from pymining.common.configuration import Configuration
from pymining.preprocessor.chisquare_filter import ChiSquareFilter
from pymining.classifier.naive_bayes import NaiveBayes
from pymining.classifier.lda import Lda
if __name__ == "__main__":
config = Configuration.FromFile("conf/test.xml")
GlobalInfo.Init(config, "__global__")
txt2mat = Text2Matrix(config, "__matrix__")
[trainx, trainy] = txt2mat.CreateTrainMatrix("data/cluster.200")
chiFilter = ChiSquareFilter(config, "__filter__")
chiFilter.TrainFilter(trainx, trainy)
[trainx, trainy] = chiFilter.MatrixFilter(trainx, trainy)
lda = Lda(config, "lda")
lda.Train(trainx, trainy, 10)
#import scipy comp
from scipy import *
#import pymining module
from pymining.math.pca import Pca
from pymining.math.matrix import Matrix
from pymining.math.text2matrix import Text2Matrix
from pymining.preprocessor.chisquare_filter import ChiSquareFilter
from pymining.common.global_info import GlobalInfo
from pymining.common.configuration import Configuration
if __name__ == "__main__":
#get pca
config = Configuration.FromFile("conf/test.xml")
GlobalInfo.Init(config, "__global__", False)
txt2mat = Text2Matrix(config, "__matrix__", False)
[trainx, trainy] = txt2mat.CreateTrainMatrix("data/train.txt")
chiFilter = ChiSquareFilter(config, "__filter__")
chiFilter.TrainFilter(trainx, trainy)
[trainx, trainy] = chiFilter.MatrixFilter(trainx, trainy)
pca = Pca()
pca.TrainPrinComp(trainx, 2, True, False)
prinCompX = pca.GetPrinComp(trainx, "col")
#set colors
colors = []
for y in trainy:
if (y == 0):